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Team Fernando-Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection

Title
Team Fernando-Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection
Type
Article in International Conference Proceedings Book
Year
2019
Authors
Cruz, AF
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Rocha, G
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Silva, RS
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Conference proceedings International
Pages: 999-1003
13th International Workshop on Semantic Evaluation
Minneapolis, Minnesota, USA , June 6–7, 2019
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Authenticus ID: P-00W-505
Abstract (EN): This paper describes our submission1 to the SemEval 2019 Hyperpartisan News Detection task. Our system aims for a linguistics-based document classification from a minimal set of interpretable features, while maintaining good performance. To this goal, we follow a feature-based approach and perform several experiments with different machine learning classifiers. On the main task, our model achieved an accuracy of 71.7%, which was improved after the task's end to 72.9%. We also participate in the meta-learning sub-task, for classifying documents with the binary classifications of all submitted systems as input, achieving an accuracy of 89.9%.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 4
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